We present a new family of proximal point methods for solving monotone variational inequalities. Our algorithm has a relative error tolerance criterion in solving the proximal subp...
Abstract. Kernel based methods (such as k-nearest neighbors classifiers) for AI tasks translate the classification problem into a proximity search problem, in a space that is usu...
We consider clustering as computation of a structure of proximity relationships within a data set in a feature space or its subspaces. We propose a data structure to represent suc...
This paper proposes to transform data scanned randomly in a well-defined space (e.g, Euclidean) along a hierarchical irregular pyramidal structure in an attempt reduce search time...